Are you interested in robotics and 4th Industrial Revolution? Do you like to publish journal papers on the area of additive manufacturing? Would you like to collaborate with the industrial partners who are leading Aerospace, Oil&Gas, Nuclear and High-Value Manufacturing sectors? Do you want to contribute to the post-COVID recovery plan? Please then read the full description and apply for this interesting PhD supported by EPSRC.
Robotics; Non-destructive Testing & Evaluation (NDT&E); Additive Manufacturing; Welding; Industry 4.0; Automated Inspection; Finite Element Simulation; Process Modelling; Post-COVID Recovery Plan.
This project aligns directly with one key deliverable in the 5-year plan entitled “Towards Industry 4.0: In-process Repair of Welding and Wire Additive Manufacturing (IRWWAM)” associated with the new Strathclyde Chancellor’s Fellow joint appointment between the EEE and DMEM for the primary supervisor (Dr Javadi). The core of this ambitious plan is fully automated Non-Destructive Evaluation (NDE) in robotic welding and Wire Arc Additive Manufacturing (WAAM), where the three main research themes are: (I) in-process defect detection, (II) in-process residual stress measurement and (III) in-process material evaluation. When these three core research themes are coupled with process modelling and simulation, the project will deliver an Industry 4.0 adopted system in which the sample can be fully inspected and importantly, repaired during the manufacturing process, if deemed necessary by the system. The in-situ measurement systems will be also linked to the manufacturing system for improving the quality control and creation of a closed-loop feedback system. Manufacturing within the IRWWAM framework will save time and energy (which is usually wasted in backward transmissions between the manufacturing and inspection stations) and hence will be better for the environment. The main plan is then in line with the national UK government post-COVID recovery plan.
This PhD will focus on the in-process monitoring of the material evolution during welding and additive manufacturing. The necessity of “in-process” evaluation has been justified by Center for Ultrasonic Engineering (CUE) when the in-process inspection was established for the multi-pass welding [Javadi et al, Materials & Design, Volume 191, 2020]. However, this was not extended to the material evaluation and there is currently no NDT method to monitor the material evolution during the welding and additive manufacturing. The in-process material evaluation will be considered in this project and it is then desired that the candidate is familiar with (or enthusiastic to learn) the following research and technical activities: NDE material evaluation, finite element simulation, process modelling and verification, in-process inspection, in-process repair, and Industry 4.0.
The project will be based in the new Faculty of Engineering facility “Robotically Enabled Sensing (RES)” laboratory and will link directly with the NDE research team operating within CUE and its Technology & Innovation Centre (TIC) laboratories. There is an excellent opportunity to enhance the capabilities of the world’s first automated robotic AM facility with integrated NDE (RoboWAAM cell currently being installed at AFRC) through the output of this project. Hence, there is an obvious route into the AFRC, Lightweight Manufacturing Centre (LMC) and National Manufacturing Institute Scotland (NMIS) activities and industrial network. Through CUE, the project will complement Strathclyde’s current The UK Research Centre in NDE (RCNDE) research, which will offer opportunities to collaborate within the RCNDE academic and industrial membership. There will also be both training and collaboration opportunities within the CDTs hosted with FUSE, FIND and Advanced Photonics.
The supervisory team are uniquely placed to provide this PhD student with direct access to a broad range of technical expertise and highly specialised facilities discussed above. Professor Jorn Mehnen, who is leading Advanced Digital Manufacturing at Strathclyde, will supervise the whole research activities to be aligned with the idea of digital manufacturing and Industry 4.0. Dr Javadi holds a joint appointment between EEE and DMEM which are directly contributing to this PhD proposal and then exceptional support and access to the strategic facilities in both departments will be available for the successful candidate.
This PhD project is run jointly with the departments of Electronic & Electrical Engineering (EEE) and the Department of Design, Manufacturing & Engineering Management (DMEM).
Electrical & Electronic
Aeronautical, Maritime and Transport Engineering
AI & Machine Learning
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